ArticleFrontiers in artificial intelligence2025
A multidimensional comparison of ChatGPT, Google Translate, and DeepL in Chinese tourism texts translation: fidelity, fluency, cultural sensitivity, and persuasiveness.
Article in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Universal interventions to improve young children's mental well-being: A systematic review and meta-analysis.Psychological bulletin · 2026Pooled it
- Navigating AI feedback in translation training: how text type, proficiency, and attitude shape students' acceptance behaviors.Frontiers in artificial intelligence · 2026Article
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2 authors.
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Abstract
This study systematically compares the translation performance of ChatGPT, Google Translate, and DeepL on Chinese tourism texts, focusing on two prompt-engineering strategies. Using a mixed-methods approach that combines quantitative expert assessments with qualitative analysis, the evaluation centers on fidelity, fluency, cultural sensitivity, and persuasiveness. ChatGPT outperformed its counterparts across all metrics, especially when culturally tailored prompts were used. However, it occasionally introduced semantic shifts, highlighting a trade-off between accuracy and rhetorical adaptation. Despite its strong performance, human post-editing remains necessary to ensure semantic precision and professional standards. The study demonstrates ChatGPT's potential in domain-specific translation tasks while calling for continued oversight in culturally nuanced content.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.